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Record W1963553919 · doi:10.1103/physreve.74.041808

Depletion interaction between two colloidal particles in a nonadsorbing polymer solution

2006· article· en· W1963553919 on OpenAlexafffund
Shuang Yang, Dadong Yan, Hong-Ge Tan, An‐Chang Shi

Bibliographic record

VenuePhysical Review E · 2006
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsColloidPolymerSolvencyChemical physicsMaterials scienceColloidal particleDepletion regionChemistryNanotechnologyPhysical chemistryComposite material

Abstract

fetched live from OpenAlex

The depletion effect between two spherical colloidal particles in nonadsorbing polymer solutions is investigated using the self-consistent field theory. The density distributions of polymer segments, the depleted amount and depletion potential are calculated numerically in bispherical coordinates. The effects of chain length, bulk concentration, and solvency are also investigated. In the dilute regime the depleted amount and the depletion potential decrease as the two spherical particles approach to each other. The depth of interaction increases and the width of interaction varies slightly with increasing bulk concentrations. In the semidilute regime, with increasing bulk concentrations the width of interaction decreases and the depth of interaction increases. No distinct repulsive potential is observed in semidilute regime. However, at high concentration the depleted amount exhibits a barrier. The width and the depth of depletion potential increase with increasing the chain length and the solvency. The contact potential is proportional to the polymer concentration and almost independent on the solvency. In addition, the effect of depletion interaction on colloidal stability is analyzed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.305
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2006
Admission routes2
Has abstractyes

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